Physical Layer High Spectrum Efficiency Technologies for 6G Networks: Orbital Angular Momentum and Reconfigurable Intelligent Surface

The next 6G wireless communication networks is expected to connect everything, provide full-dimensional wireless coverage, and integrate all functions to support full-vertical applications. Hence, the 6G network is required to process massive amounts of data in near real time, with extremely high throughput and low latency. To achieve these performance metrics, lots of novel enabling technologies will be used in 6G networks. Among many potential technologies, the orbital angular momentum (OAM) with new degrees of freedom and the reconfigurable intelligent surface (RIS) with wireless environment control capability are the most competitive. Specifically, the phase fronts of electromagnetic (EM) waves carrying different OAM modes rotate with azimuth exhibiting a set of mutually orthogonal helical structures in space. These orthogonal helical phase structures provide a new degree of freedom for both information transmission and radar application. Besides, the RIS is a planar array with a massive number of low-cost passive reflecting elements, which can intelligently control the EM wavefront, such as phase, amplitude, frequency, and even polarization, by intelligently adjusting these passive elements. Both of the above technologies provide potential solutions for improving the spectrum efficiency (SE) and energy efficiency (EE) of 6G networks. However, there are still many technical challenges for the practical application of OAM and/or RIS wireless communications, such as the generation and reception of multi-mode OAM beams, the alignment and detection of multi-mode OAM signals, the integration of OAM division multiplexing and existing multiple-input multiple-output (MIMO) communications, and the channel estimation of RIS-aided communication with interference. To address the above issues, we 1. propose an overall scheme of the line-of-sight multi-carrier and multi-mode OAM (LoS MCMM-OAM) single-user wireless communication based on uniform circular arrays (UCAs) in Chapter 2. A salient feature of the proposed system is that its channel matrix is completely characterized by three parameters, namely, the azimuth angle, the elevation angle and the distance, independent of the numbers of subcarriers and antennas. In Chapter 2, we first verify that UCA can generate multi-mode OAM radio beam with both the radio frequency (RF) analog synthesis method and the baseband digital synthesis method. After that, for the considered UCA-based LoS MCMM-OAM communication system, two distance and angle of arrival (AoA) estimation methods based on the estimating signal parameter via rotational invariance (ESPRIT) algorithm are proposed and compared to obtain the channel state information (CSI). The proposed estimation methodes significantly reduce the burden by avoiding estimating a large channel matrix, compared to the conventional MIMO-OFDM systems. Afterwards, we propose an OAM reception scheme including the beam steering with the estimated AoA and the amplitude detection with the estimated distance. At last, the proposed methods are extended to the LoS MCMM-OAM-MIMO system equipped with uniform concentric circular array (UCCAs). Both mathematical analysis and simulation results validate that the proposed OAM reception scheme can mitigate the inter-mode interference of a practical misaligned OAM channel and approaches the performance of an ideally aligned OAM channel. 2. present an overall scheme of the downlink multi-user OAM (MU-OAM) wireless backhaul based on UCAs in Chapter 3, which achieves the joint spatial division and coaxial multiplexing (JSDCM) by integrating existing MIMO technology. Similar to the single-user OAM system, the channel matrix of the proposed MU-OAM system is completely characterized by the position of each small base station (SBS), independent of the numbers of subcarriers and antennas. Thereafter, we propose an MU-OAM distance and AoA estimation method, which is able to simultaneously estimate the positions of multiple SBSs with a flexible number of training symbols. With the estimated distances and AoAs, a MU-OAM preprocessing scheme is applied to eliminate the co-mode and inter-mode interferences in the downlink MU-OAM channel. At last, the proposed methods are extended to the downlink MU-OAM-MIMO wireless backhaul system equipped with UCCAs, for which much higher SE and EE than traditional MU-MIMO systems can be achieved. Both mathematical analysis and simulation results validate that the proposed scheme can effectively eliminate both interferences of the practical downlink MU-OAM channel and approaches the performance of the ideal MU-OAM channel. 3. design the first integrated OAM radar-communication (RadCom) scheme based on UCAs in Chapter 4, which modulates information signals on the existing OAM radar waveform. In details, we first propose an OAM-based three-dimensional (3-D) super-resolution position estimation and rotation velocity detection method, which can accurately estimate the 3-D position and rotation velocity of multiple targets without beam scanning. Then, we derive the posterior Cramer-Rao bound (PCRB) of the estimated parameters mentioned above and, finally, we analyze SE of the integrated system. To achieve the best trade-off between imaging and communication, the transmitted integrated OAM beams are optimized by means of an exhaustive search method. Both mathematical analysis and simulation results show that the proposed radar-centric joint OAM RadCom scheme can accurately estimate the 3-D position and rotation velocity of multiple targets while ensuring the SE of the communication receiver, which can be regarded as an effective supplement to existing joint RadCom schemes. 4. consider the channel estimation problem when a RIS with interference is used to aid wireless communications in Chapter 5. Specifically, the interference is divided into two types: the slow-varying interference from other user equipments and the fast-varying interference from environmental noise. Firstly, to address the slow-varying interference, we make use of a two-stage training phase that, for any RIS configuration, operates as follows. In the first phase, the user equipment is not transmitting and the base station estimates the interference contribution that reaches it. This is then subtracted in the second phase during which the cascaded channel from the user equipment to the base station through each RIS element is estimated. In doing so, a-priori knowledge of the interference and cascaded channel is not required as a conservative reduced-subspace least square (RS-LS) estimator is utilized. Moreover, we also consider a fast-varying interference, which can be viewed as a temporally white zero mean Gaussian stationary noise. This type of interference cannot be removed using the aforementioned methods. To address this interference, with the assumption of known second-order statistics of the interference and channel, the linear minimum mean square error (LMMSE) estimator, which possesses excellent anti-interference capabilities, is applied to accurately estimate the cascaded channel. After that, the mean-square-error (MSE) of channel estimates is computed and used to optimize the phase-shift configurations of RIS elements in different interference scenarios. Numerical results prove the effectiveness of the proposed approaches in slow- or fast-varying interference scenarios.